Microsoft MB-260 Exam Dumps & Practice Test Questions

Question 1:

As a Customer Data Platform Specialist, you need to establish relationships between entities to help the marketing team build segments and metrics. 

Which three types of relationships are available in Audience Insights? (Select all that apply.)

A Non-editable system relationships created during the data unification process
B Non-editable system relationships created automatically during data ingestion
C Editable inherited relationships created during data unification
D Editable custom relationships created and managed by users
E Non-editable inherited relationships automatically created from ingested data sources

Correct answers: A, D, E

Explanation:

In Microsoft Dynamics 365 Customer Insights (formerly Audience Insights), defining relationships between entities (or tables) is essential to combine and analyze data from different sources effectively. These relationships are the backbone for creating customer segments, calculating measures, and generating insights that support marketing efforts.

There are three main types of relationships in the system: system relationships, inherited relationships, and custom relationships. These can be either editable or non-editable depending on how they are generated and maintained.

Option A refers to non-editable system relationships that are created automatically by the platform during the data unification process. These relationships are generated by matching unique identifiers across datasets to unify customer records. Because these relationships form the foundation of unified data, they cannot be changed by users.

Option D represents editable custom relationships that users create manually. Users can specify which fields connect different entities, offering flexibility to link data sources that don’t naturally unify. These relationships can be modified or deleted by users as needed.

Option E describes non-editable inherited relationships which are automatically detected when ingesting data. They originate from foreign key constraints or references within the source systems and are preserved in Customer Insights to reflect the original data model. These inherited relationships cannot be altered by users.

Option B is incorrect because system relationships are tied more closely to the unification process rather than ingestion alone. Option C is incorrect because inherited relationships are always non-editable to maintain data integrity and source alignment.

Therefore, the available relationship types in Audience Insights include non-editable system relationships (A), editable custom relationships (D), and non-editable inherited relationships (E). Understanding these categories helps users effectively manage entity connections for accurate segmentation and measurement.

Question 2:

As a Customer Data Platform Specialist in a B2B-focused company, you are tasked with implementing Audience Insights to support business account scenarios. 

Which statement accurately describes the differences between handling business accounts and individual consumers in Audience Insights?

A The default product recommendation model supports business accounts.
B Data ingestion features differ for business accounts compared to individual customers.
C Certain enrichment types are exclusive to individual customers, while others are specific to business accounts.
D Business accounts and individual consumers share the exact same Audience Insights environment.

Correct answer: C

Explanation:

Microsoft Dynamics 365 Customer Insights is designed to accommodate both business-to-consumer (B2C) and business-to-business (B2B) scenarios. However, the way it processes, enriches, and utilizes data varies significantly depending on whether the focus is on individual consumers or business accounts.

Option C correctly identifies that some enrichment types are tailored specifically for individual customers, while others are designed for business accounts. For example, consumer-focused enrichments like brand affinity and interest data leverage personal preferences and behaviors, which are relevant for B2C marketing. These enrichments draw on datasets that describe individual-level engagement patterns and online activity.

On the other hand, firmographic enrichments—such as industry classification, company size, or revenue estimates—are pertinent for B2B scenarios. These enrichments help organizations understand business account profiles and tailor marketing strategies to company characteristics rather than individual attributes.

Option A is incorrect because the out-of-the-box product recommendation model is optimized for individuals, not business accounts. Applying it directly to B2B data without customization would not yield accurate or actionable insights.

Option B is misleading since the data ingestion process remains largely consistent regardless of whether the data pertains to business accounts or individuals. The core difference lies in how the data is modeled and which enrichments are applied.

Option D is somewhat true because both business accounts and individual consumer data can reside in the same environment, but it does not highlight the critical differences in feature availability and enrichment capabilities.

In summary, the key point is that enrichment types differ depending on whether the data represents individuals or business accounts, making option C the most accurate choice. This understanding ensures the platform is used effectively to meet the unique needs of B2B marketing.

Question 3:

As a Customer Data Platform Specialist, your company’s Chief Marketing Officer (CMO) wants to learn how Dynamics 365 Customer Insights engagement insights can enhance audience insights. 

Which two statements accurately describe the advantages of engagement insights? (Choose two.)

A. It enables tracking, measuring, and understanding customer behavior on your website.
B. It allows the creation of new customer profiles directly within engagement insights for export to audience insights.
C. It enables sending new customer leads straight to a marketing automation system.
D. It supports linking audience insights and engagement insights environments to allow bidirectional data exchange.

Correct Answers: A, D

Explanation:

Engagement insights in Dynamics 365 Customer Insights is designed to capture detailed behavioral data from digital touchpoints, such as websites and mobile apps. This data layer adds significant value when combined with audience insights, which unify and enrich customer profiles by consolidating data from various sources.

Option A is accurate because engagement insights primarily focuses on collecting and analyzing customer interactions on digital channels. This includes tracking behaviors like page views, clicks, and navigation patterns, which provide marketing teams with a deeper understanding of how customers engage with online content. This behavioral intelligence complements the unified customer profiles in audience insights, allowing marketers to better segment audiences and personalize experiences based on actual engagement.

Option D is also correct. Linking the engagement insights environment with audience insights enables a more integrated data flow, where real-time behavioral data can enhance the unified customer profiles. Although not all data flows bidirectionally, this integration helps marketers combine static demographic or transactional data with dynamic interaction data for improved segmentation and personalization.

Option B is incorrect because engagement insights does not independently create customer profiles; instead, it enriches existing profiles within audience insights by providing behavioral data.

Option C is incorrect since engagement insights is not responsible for pushing leads to marketing automation platforms. That function typically falls to other components, such as Dynamics 365 Marketing, which operates on unified profiles and segments.

In summary, engagement insights enhances audience insights by providing behavioral data (A) and linking environments for comprehensive data integration (D), making these two options correct.

Question 4:

The IT department wants to better understand key considerations when analyzing Dynamics 365 Customer Insights data using Microsoft Azure Synapse Analytics. 

Which three statements correctly outline important points to consider? (Select three.)

A. Exporting data based on the Common Data Model folder format is supported when configuring Azure Synapse Analytics export.
B. Administrator access in Dynamics 365 Customer Insights is necessary to establish the connection with Azure Synapse Analytics.
C. Scheduled data refreshes disable any updates to existing Azure Synapse connections.
D. Data exports to Azure Synapse Analytics can occur both on demand and via scheduled refreshes.
E. Dynamics 365 Customer Insights data can be ingested and used within Azure Synapse Analytics.

Correct Answers: A, B, D

Explanation:

When integrating Dynamics 365 Customer Insights with Azure Synapse Analytics for advanced data analysis, it is critical to understand how the data export and access mechanisms work to ensure a smooth and secure setup.

Option A is correct because data exports from Customer Insights to Synapse use the Common Data Model (CDM) folder format. This format standardizes data structure and metadata, making it easier to manage, query, and analyze data within Azure Synapse Analytics using compatible tools. Employing CDM ensures that the exported data is consistent and readily interpretable.

Option B is also true. Configuring the connection between Dynamics 365 Customer Insights and Azure Synapse Analytics requires administrative privileges. This is necessary to handle authentication, resource management, and secure integration, preventing unauthorized users from accessing or modifying the data export setup.

Option C is incorrect. Scheduled refreshes do not block or disable updates to existing Azure Synapse connections. Instead, scheduled refreshes enable automated, regular updates to data exports, ensuring that the data in Synapse remains current without manual intervention. Connections can still be managed and updated as needed even if scheduled refreshes are active.

Option D is correct because Dynamics 365 Customer Insights supports both manual (on-demand) exports and automated scheduled refreshes to Azure Synapse Analytics. This flexibility allows IT teams to choose whether to update data in Synapse instantly or at regular intervals based on business needs.

Option E is somewhat true but too vague. While Customer Insights data can indeed be ingested and analyzed in Azure Synapse once exported, this statement does not convey a technical or procedural consideration necessary during setup. It describes a capability rather than a planning or configuration point.

To summarize, the IT team should prioritize using the CDM format for export (A), ensure proper administrative access for setup (B), and understand that data exports can be triggered on demand or scheduled (D) for seamless integration with Azure Synapse Analytics.

Question 5:

When implementing Microsoft Dynamics 365 Customer Insights for a company primarily operating in the B2B space, what key factor should you consider regarding business accounts versus individual consumers?

A. Rolling up sub-accounts is not supported when creating measures for business accounts.
B. Certain enrichment types are exclusive to individual customers, while others apply only to business accounts.
C. Data unification for business accounts automatically configures account hierarchies.
D. Data ingestion differs between business accounts and individual customers.

Correct Answer: B

Explanation:

Microsoft Dynamics 365 Customer Insights is designed to support both B2C (business-to-consumer) and B2B (business-to-business) environments, but it handles data and enrichment differently depending on whether the focus is on individual consumers or business accounts. When setting up Customer Insights for a B2B company, it is crucial to understand these distinctions, particularly around how enrichment features work.

Option B is correct because the platform offers different enrichment options tailored to the customer type. For individual consumer data, enrichment might include demographic details, interests, or behavioral traits pulled from consumer datasets. Conversely, business accounts are enriched with firmographic data like company size, industry classification, and company hierarchy. These enrichment types are designed specifically for their respective customer categories and are not interchangeable. Recognizing which enrichment applies to individuals versus businesses helps ensure accurate and meaningful customer insights.

Option A is incorrect because Dynamics 365 Customer Insights does support hierarchical data structures for business accounts. This means you can roll up data from sub-accounts under a parent company to create aggregate measures and insights.

Option C is false because while hierarchies can be defined in Customer Insights, the system does not automatically create these account hierarchies during data unification. Users need to explicitly model and configure these relationships.

Option D is inaccurate because data ingestion processes are consistent regardless of whether the data pertains to individuals or business accounts. The difference lies in how the data is modeled and enriched after ingestion, not in the ingestion process itself.

In summary, understanding the availability of different enrichment types based on customer profile (individual vs. business) is critical for correctly setting up and using Dynamics 365 Customer Insights in B2B scenarios, making B the correct answer.

Question 6:

Your company markets pet accessories and personalizes emails based on customer interest in cats and dogs and their country. 

Which measure from Microsoft interests enrichment should you recommend for creating a customer segment focused on those more interested in dogs than cats across different countries?

A. Interest affinity score
B. Interest share of voice score
C. Interest share of voice country demographic segment
D. Interest affinity level

Correct Answer: A

Explanation:

In this scenario, the marketing team needs to identify customers whose interest in dogs surpasses their interest in cats, with the additional filter of geographic location. Microsoft’s interests enrichment provides multiple outputs, but the interest affinity score is the most precise and useful for this requirement.

The interest affinity score quantifies how strongly an individual customer is associated with a particular interest relative to other interests. This numeric score allows direct comparison between interests for each customer, making it possible to segment those with a higher affinity for dogs than cats accurately. Because it is a continuous, granular measure, marketers can perform detailed and personalized segmentation based on individual preferences.

Option B, the interest share of voice score, is more relevant for analyzing the overall attention a topic gets in media or social channels. It does not represent individual customer interest levels and so is not useful for creating personalized segments.

Option C, the interest share of voice country demographic segment, aggregates interest data at a population or demographic level by country. While valuable for high-level trend analysis, it cannot help compare interests at the individual customer level.

Option D, the interest affinity level, categorizes interest into broad groups (e.g., low, medium, high). While simpler, this lacks the fine granularity needed for detailed, comparative segmentation based on multiple interests.

Therefore, A is the best choice because it enables the marketing team to quantitatively compare individual customers’ interests and build highly targeted segments that factor in both interest levels and geographic differences.

Question 7:

A service agent notices that while recent online orders appear immediately in the Dynamics 365 Customer Insights timeline, the total order amount shown in the system does not update accordingly. 

What is the best explanation for this behavior?

A. Real-time ingested data is filtered out when defining the measurement.
B. Real-time ingested data contains limited details, possibly including the order amount.
C. Real-time data must be refreshed before the measures get updated.
D. Real-time ingested activities are visible on the timeline but excluded from measure calculations.

Correct answer: D

Explanation:

Microsoft Dynamics 365 Customer Insights supports both batch and real-time data ingestion. This allows the platform to show immediate data updates—like new orders—in the customer timeline to provide front-line teams quick access to the latest customer activities. However, it is important to understand the distinction between data visibility and data aggregation for analytics.

In this scenario, the recent online orders are displayed in real time on the timeline, allowing service representatives to see customer activity without delay. However, these real-time activities are not immediately integrated into backend calculations such as aggregated measures, KPIs, or total order amounts. Those measures depend on data processed through batch refresh cycles, where data is validated, cleaned, and consolidated into analytic models.

Answer A assumes a filtering issue, but no indication of such filtering is provided here, so it’s unlikely.
Answer B highlights limited data in real-time ingestion, but this does not explain why measures fail to update since the issue is not missing attributes but calculation exclusion.
Answer C is close but misleading—real-time data does not simply need a refresh; it is architecturally excluded from immediate aggregation until batch processes complete.
Answer D correctly explains that real-time activities are shown immediately for visibility but excluded from measure calculations until they undergo scheduled data processing. This design ensures that measures remain consistent, accurate, and based on fully validated data rather than potentially incomplete or transient real-time inputs.

Thus, the most accurate explanation for the observed discrepancy is that real-time ingested data is visible instantly but excluded from measurement calculations until batch processing occurs, making D the correct answer.

Question 8:

When implementing Microsoft Dynamics 365 Customer Insights for a business primarily operating in B2B, what key factor should be considered when managing business accounts versus individual consumer profiles?

A. The product recommendation model provided out-of-the-box supports business accounts.
B. Different enrichment types are available specifically for individual consumers versus business accounts.
C. Account hierarchies can only be applied when working with segments and measures.
D. Business accounts and individual consumers operate in the same Customer Insights environment.

Correct answer: B

Explanation:

Microsoft Dynamics 365 Customer Insights distinguishes between individual consumer profiles and business accounts (organizations), recognizing that these two customer types have different data needs and enrichment capabilities. When deploying Customer Insights in a B2B context, understanding these differences is essential for effective data management and customer intelligence.

Answer A is incorrect because the default product recommendation prediction model is designed for individual consumers based on behavioral patterns like past purchases or interactions, typical of B2C scenarios. It is not optimized for business accounts, which usually require firmographic data and relationship hierarchies rather than behavioral signals.

Answer C is also inaccurate; account hierarchies are widely used beyond just segments and measures. They are crucial for representing parent-child relationships among business entities in B2B, affecting personalization, reporting, and insight generation across various features.

Answer D is factually true—both business accounts and individuals coexist in the same Customer Insights environment—but this does not address the specific functional considerations when managing these distinct profile types.

Answer B correctly identifies that certain enrichment types are tailored to profile types: for example, demographic enrichment like age and gender applies to individual consumers, while firmographic enrichment such as industry, company size, and revenue applies to business accounts. This distinction affects the kind of intelligence, segmentation, and analysis you can perform and is a crucial consideration when setting up Customer Insights for a B2B company.

In summary, understanding which enrichments and features apply to business accounts versus individuals enables you to better tailor your Customer Insights implementation for your organization’s unique data and business model. Hence, B is the best answer.

Question 9:

Your company wants to enhance its marketing campaigns by creating targeted customer segments based on behaviors such as purchase history and website activity. 

Which Customer Insights feature allows you to group customers based on specific attributes and behaviors?

A. Data ingestion
B. Customer data unification
C. Customer segmentation
D. Predictive analytics

Correct answer: C

Explanation:

In the MB-260 exam, understanding how to use customer segmentation within Microsoft Dynamics 365 Customer Insights is essential. Customer segmentation is the process of dividing customers into groups based on shared characteristics, such as demographics, purchasing habits, or engagement levels.

Option C, Customer segmentation, is the correct answer because it enables marketers to create meaningful groups that can be targeted with personalized campaigns. For example, customers who frequently purchase a particular product category or who have recently engaged with the website can be segmented to receive relevant offers. This helps improve campaign effectiveness by delivering tailored messages that resonate with each segment’s preferences.

Option A, Data ingestion, refers to the process of importing customer data from various sources into Customer Insights but does not involve grouping or segmenting customers.

Option B, Customer data unification, focuses on merging and resolving duplicate customer records to form a single, accurate profile but does not create groups for marketing.

Option D, Predictive analytics, involves using machine learning models to forecast customer behavior or churn risk but comes after segmentation.

Effectively leveraging customer segmentation is vital in MB-260 as it drives targeted marketing and personalized customer experiences. It also improves ROI by focusing resources on the most relevant customer groups.

Question 10:

You need to import customer data from multiple external systems into Dynamics 365 Customer Insights. 

Which process ensures that the data is correctly formatted, cleansed, and ready for analysis?

A. Identity resolution
B. Data ingestion and transformation
C. Customer segmentation
D. Predictive modeling

Correct answer: B

Explanation:

A core component of MB-260 is understanding how to bring in data from various external sources to create a unified customer view. The process that ensures data from these sources is properly prepared is called data ingestion and transformation.

Option B, Data ingestion and transformation, is the right answer. This process involves extracting data from multiple systems (e.g., CRM, POS, social media), importing it into Customer Insights, and then transforming it — including cleaning, normalizing, and formatting the data — so it can be reliably analyzed. Without proper transformation, inconsistent or dirty data would reduce the accuracy of customer insights.

Option A, Identity resolution, follows ingestion and is responsible for merging duplicate customer records and creating unified profiles, but it does not handle data formatting or cleansing.

Option C, Customer segmentation, groups customers into segments based on attributes but assumes clean and unified data is already available.

Option D, Predictive modeling, uses advanced analytics to forecast behaviors but is a later stage after ingestion and unification.

In MB-260, mastering data ingestion and transformation is essential because it lays the groundwork for all subsequent processes—without clean, well-structured data, customer insights would be flawed. This step is critical to building an accurate and actionable 360-degree customer profile.